visa-doc-translate
Skill1 starsChanged 8 months agoMITView on GitHub
Translate visa application documents (images) to English and create a bilingual PDF with original and translation
- Installs packages
We split this skill into the rules it gives an agent
12 rules. About 0 are common, 10 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈10
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 10
When the user provides an image file path, AUTOMATICALLY execute the following steps WITHOUT asking for confirmation:
- Very specific: line 12
Image Conversion: If the file is HEIC, convert it to PNG using sips -s format png <input> --out <output>
- Distinctive: line 15
Check EXIF orientation data
- Distinctive: line 17
If EXIF orientation is 6, rotate 90 degrees counterclockwise
- Distinctive: line 31
Use professional terminology appropriate for visa applications
- Distinctive: line 32
Keep proper names in original language with English in parentheses
- Distinctive: line 37
Create a Python script using PIL and reportlab libraries
- Distinctive: line 43
Add a note at the bottom: "This is a certified English translation of the original document"
- Very specific: line 46
Output: Create a PDF file named <original_filename>_Translated.pdf in the same directory
- Distinctive: line 93
DO NOT ask for user confirmation at each step
- Distinctive: line 96
Ensure all numbers, dates, and amounts are accurately translated
- Distinctive: line 97
Use clean, professional formatting
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
You are helping translate visa application documents for visa applications.
Instructions
When the user provides an image file path, AUTOMATICALLY execute the following steps WITHOUT asking for confirmation:
- Image Conversion: If the file is HEIC, convert it to PNG using
sips -s format png <input> --out <output> - Image Rotation:
- Check EXIF orientation data
- Automatically rotate the image based on EXIF data
- If EXIF orientation is 6, rotate 90 degrees counterclockwise
- Apply additional rotation as needed (test 180 degrees if document appears upside down)
- OCR Text Extraction:
- Try multiple OCR methods automatically:
- macOS Vision framework (preferred for macOS)
- EasyOCR (cross-platform, no tesseract required)
- Tesseract OCR (if available)
- Extract all text information from the document
- Identify document type (deposit certificate, employment certificate, retirement certificate, etc.)
- Try multiple OCR methods automatically:
- Translation:
- Translate all text content to English professionally
- Maintain the original document structure and format
- Use professional terminology appropriate for visa applications
- Keep proper names in original language with English in parentheses
- For Chinese names, use pinyin format (e.g., WU Zhengye)
- Preserve all numbers, dates, and amounts accurately
- PDF Generation:
- Create a Python script using PIL and reportlab libraries
- Page 1: Display the rotated original image, centered and scaled to fit A4 page
- Page 2: Display the English translation with proper formatting:
- Title centered and bold
- Content left-aligned with appropriate spacing
- Professional layout suitable for official documents
- Add a note at the bottom: "This is a certified English translation of the original document"
- Execute the script to generate the PDF
- Output: Create a PDF file named
<original_filename>_Translated.pdfin the same directory
Supported Documents
- Bank deposit certificates (存款证明)
- Income certificates (收入证明)
- Employment certificates (在职证明)
- Retirement certificates (退休证明)
- Property certificates (房产证明)
- Business licenses (营业执照)
- ID cards and passports
- Other official documents
Technical Implementation
OCR Methods (tried in order)
- macOS Vision Framework (macOS only):
import Vision from Foundation import NSURL - EasyOCR (cross-platform):
pip install easyocr - Tesseract OCR (if available):
brew install tesseract tesseract-lang pip install pytesseract
Required Python Libraries
pip install pillow reportlabFor macOS Vision framework:
pip install pyobjc-framework-Vision pyobjc-framework-QuartzImportant Guidelines
- DO NOT ask for user confirmation at each step
- Automatically determine the best rotation angle
- Try multiple OCR methods if one fails
- Ensure all numbers, dates, and amounts are accurately translated
- Use clean, professional formatting
- Complete the entire process and report the final PDF location
Example Usage
/visa-doc-translate RetirementCertificate.PNG
/visa-doc-translate BankStatement.HEIC
/visa-doc-translate EmploymentLetter.jpgOutput Example
The skill will:
- Extract text using available OCR method
- Translate to professional English
- Generate
<filename>_Translated.pdfwith:- Page 1: Original document image
- Page 2: Professional English translation
Perfect for visa applications to Australia, USA, Canada, UK, and other countries requiring translated documents.
Other versions10 projects use a version of this.
Word for word · 10
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Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository71 other files it gives its agents.
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- docs/agents.mdAGENTS.md
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